NIPS 2014

mugSecond and last day of the NIPS workshops! The collection of topics was quite broad and would have made my choosing an ordeal, except that I was invited to give a talk at the probabilistic programming workshop, solving my dilemma… The first talk by Kathleen Fisher was quite enjoyable in that it gave a conceptual discussion of the motivations for probabilistic languages, drawing an analogy with the early days of computer programming that saw a separation between higher level computer languages and machine programming, with a compiler interface. And calling for a similar separation between the models faced by statistical inference and machine-learning and the corresponding code, if I understood her correctly. This was connected with Frank Wood’s talk of the previous day where he illustrated the concept through a generation of computer codes to approximately generate from standard distributions like Normal or Poisson. Approximately as in ABC, which is why the organisers invited me to talk in this session. However, I was a wee bit lost in the following talks and presumably lost part of my audience during my talk, as I realised later to my dismay when someone told me he had not perceived the distinction between the trees in the random forest procedure and the phylogenetic trees in the population genetic application. Still, while it had for me a sort of Twilight Zone feeling of having stepped in another dimension, attending this workshop was an worthwhile experiment as an eye-opener into a highly different albeit connected field, where code and simulator may take the place of a likelihood function… To the point of defining Hamiltonian Monte Carlo directly on the former, as Vikash Mansinghka showed me at the break.

I completed the day with the final talks in the variational inference workshop, if only to get back on firmer ground! Apart from attending my third talk by Vikash in the conference (but on a completely different topic on variational approximations for discrete particle-ar distributions), a talk by Tim Salimans linked MCMC and variational approximations, using MCMC and HMC to derive variational bounds. (He did not expand on the opposite use of variational approximations to build better proposals.) Overall, I found these two days and my first NIPS conference quite exciting, if somewhat overpowering, with a different atmosphere and a different pace compared with (small or large) statistical meetings. (And a staggering gender imbalance!)

3 Responses to “NIPS 2014”

  1. One of the things I like most is the security queue in the airport the day after NIPS, had great talks with Kevin Murphy, Dieter Fox and also saw several others by the gate. Really enjoyed having you at NIPS, with luck you’ll be back soon. Interesting to see all your thoughts, and was really pleased to see the gap between probabilistic programming and ABC start to close!

    • This was the (only) drawback with the frequent flier security queue, there was no one to talk with!!! I will certainly attempt another NIPS, even without the skiing incentive! A few more talks and I’ll be 100% clear about PP=ABC!

  2. Perfect trip back, from a nice chat with Max Welling in the Montréal lounge to a seat on the upper deck where I could sleep with flat legs on the side drawers. And hardly any delay…until I boarded the train downtown that got stuck for so long that I was 10mn late for my last class. Had to skip improper priors completely! Which will not sadden some of my readers..!

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